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Prospectively investigating the impact of AI onshared decision-making in post kidney transplant care (PRIMA-AI): protocol for a longitudinal qualitative study among patients, their support persons and treating physicians at a tertiary care centre
Sassi, Zeineb, Eickmann, Sascha, Roller, Roland, Osmanodja, Bilgin, Burchardt, Aljoscha, Samhammer, David, Dabrock, Peter, Möller, Sebastian, Budde, Klemens und Herrmann, Anne
(2024)
Prospectively investigating the impact of AI onshared decision-making in post kidney transplant care (PRIMA-AI): protocol for a longitudinal qualitative study among patients, their support persons and treating physicians at a tertiary care centre.
BMJ Open 14 (10), e081318.
Veröffentlichungsdatum dieses Volltextes: 10 Okt 2024 13:58
Artikel
DOI zum Zitieren dieses Dokuments: 10.5283/epub.59364
Zusammenfassung
Introduction As healthcare is shifting from a paternalistic to a patient-centred approach, medical decision making becomes more collaborative involving patients, their support persons (SPs) and physicians. Implementing shared decision-making (SDM) into clinical practice can be challenging and becomes even more complex with the introduction of artificial intelligence (AI) as a potential ...
Introduction As healthcare is shifting from a
paternalistic to a patient-centred
approach, medical
decision making becomes more collaborative
involving patients, their support persons (SPs) and
physicians. Implementing shared decision-making
(SDM) into clinical practice can be challenging and
becomes even more complex with the introduction
of artificial intelligence (AI) as a potential actant in
the communicative network. Although there is more
empirical research on patients’ and physicians’
perceptions of AI, little is known about the impact of AI
on SDM. This study will help to fill this gap. To the best
of our knowledge, this is the first systematic empirical
investigation to prospectively assess the views of
patients, their SPs and physicians on how AI affects
SDM in physician–patient communication after kidney
transplantation. Using a transdisciplinary approach, this
study will explore the role and impact of an AI-decision
support system (DSS) designed to assist with medical
decision making in the clinical encounter.
Methods and analysis This is a plan to roll out a 2 year,
longitudinal qualitative interview study in a German
kidney transplant centre. Semi-structured
interviews
with patients, SPs and physicians will be conducted
at baseline and in 3-, 6-, 12- and 24-month
follow-up.
A total of 50 patient–SP dyads and their treating
physicians will be recruited at baseline. Assuming a
dropout rate of 20% per year, it is anticipated that 30
patient–SP dyads will be included in the last follow-up
with the aim of achieving data saturation. Interviews will
be audio-recorded
and transcribed verbatim. Transcripts
will be analysed using framework analysis. Participants
will be asked to report on their (a) communication
experiences and preferences, (b) views on the influence
of the AI-based
DSS on the normative foundations of
the use of AI in medical decision-making,
focusing on
agency along with trustworthiness, transparency and
responsibility and (c) perceptions of the use of the AI-based
DSS, as well as barriers and facilitators to its
implementation into routine care.
Ethics and dissemination Approval has been
granted by the local ethics committee of Charité—
Universitätsmedizin Berlin (EA1/177/23 on 08 August
2023). This research will be conducted in accordance
with the principles of the Declaration of Helsinki
(1996). The study findings will be used to develop
communication guidance for physicians on how to
introduce and sustainably implement AI-assisted
SDM.
The study results will also be used to develop lay
language patient information on AI-assisted
SDM. A
broad dissemination strategy will help communicate
the results of this research to a variety of target groups,
including scientific and non-scientific
audiences, to
allow for a more informed discourse among different
actors from policy, science and society on the role and
impact of AI in physician–patient communication.
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| Dokumentenart | Artikel | ||||
| Titel eines Journals oder einer Zeitschrift | BMJ Open | ||||
| Verlag: | BMJ | ||||
|---|---|---|---|---|---|
| Band: | 14 | ||||
| Nummer des Zeitschriftenheftes oder des Kapitels: | 10 | ||||
| Seitenbereich: | e081318 | ||||
| Datum | 1 Oktober 2024 | ||||
| Institutionen | Medizin > Institut für Epidemiologie und Präventivmedizin > Medizinische Soziologie | ||||
| Identifikationsnummer |
| ||||
| Dewey-Dezimal-Klassifikation | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin | ||||
| Status | Veröffentlicht | ||||
| Begutachtet | Ja, diese Version wurde begutachtet | ||||
| An der Universität Regensburg entstanden | Ja | ||||
| URN der UB Regensburg | urn:nbn:de:bvb:355-epub-593647 | ||||
| Dokumenten-ID | 59364 |
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